Regulation of Cytosolic Phospholipase A2 (cPLA2) and Its Association with Cell Proliferation in Human Lens Epithelial Cells

PURPOSE. To investigate the molecular mechanism for cytosolic phospholipase A2 (cPLA2) regulation and its association to platelet-derived growth factor (PDGF)-induced cell proliferation. METHODS. cPLA2 was examined using human lens epithelial (HLE) B3 cells. Reactive oxygen species (ROS) generation induced by PDGF was analyzed by luminescence assay. Cell proliferation was measured by cell counting and by BrdU assay. Human cPLA2 gene was cloned via RT-PCR followed by sitedirected mutagenesis to construct HLE B3 cells expressing either inactive cPLA2 enzyme with S228A mutation (S228A), or cPLA2 truncated at the calcium-binding C2 domain (C2D). Activity of cPLA2 was measured by arachidonic acid (AA) release from cell membranes using [3H]-arachidonic acid prelabeled cells. The effect of intracellular calcium level on cPLA2 function was examined by treating cells with ionomycin (calcium influx), thapsgargin (endoplasmic reticulum [ER] calcium store release) or 1,2-bis(o-aminophenoxy)ethane-N,N,N,N-tetraacetic acid tetrakis (BAPTA; calcium chelator). Activation of extracellular signal–regulated kinases (ERK), JNK, p38, or Akt was detected by Western blot analysis using specific antibodies. RESULTS. S228A mutant showed suppressed PDGF-induced reactive oxygen species generation, ERK and JNK activation (no effect on p38 or Akt), and cell proliferation in comparison with the vector alone (Vec) control. Calcium-binding C2 domain cells lost the ability of membrane translocation and activation of cPLA2. PDGF cell signaling was calcium-dependent, and the calcium was supplied either from the external flux or endoplasmic reticulum store. However, enrichment of cellular calcium not only augmented PDGF function, but also demonstrated a cPLA2-dependent calcium-signaling cascade that led to cell proliferation. CONCLUSIONS. cPLA2 is regulated by calcium mobilization and mitogen-activated protein kinases (MAPK) activation. Both PDGF mitogenic action and calcium signaling are cPLA2-dependent

SBVLC:Secure Barcode-based Visible Light Communication for Smartphones

2D barcodes have enjoyed a significant penetration rate in mobile applications. This is largely due to the extremely low barrier to adoption – almost every camera-enabled smartphone can scan 2D barcodes. As an alternative to NFC technology, 2D barcodes have been increasingly used for security-sensitive mobile applications including mobile payments and personal identification. However, the security of barcode-based communication in mobile applications has not been systematically studied. Due to the visual nature, 2D barcodes are subject to eavesdropping when they are displayed on the smartphone screens. On the other hand, the fundamental design principles of 2D barcodes make it difficult to add security features. In this paper, we propose SBVLC - a secure system for barcode-based visible light communication (VLC) between smartphones. We formally analyze the security of SBVLC based on geometric models and propose physical security enhancement mechanisms for barcode communication by manipulating screen view angles and leveraging user-induced motions. We then develop three secure data exchange schemes that encode information in barcode streams. These schemes are useful in many security-sensitive mobile applications including private information sharing, secure device pairing, and contactless payment. SBVLC is evaluated through extensive experiments on both Android and iOS smartphones

A parallel self-organizing community detection algorithm based on swarm intelligence for large scale complex networks

Community detection is a critical task for complex network analysis. It helps us to understand the properties of the system that a complex network represents and has significance to a wide range of applications. Nowadays, the challenges faced by community detection algorithms include overlapping community structure detection, large scale network analysis, dynamic changing of analyzed network topology and many more. In this paper a self-organizing community detection algorithm, based on the idea of swarm intelligence, was proposed and its parallel algorithm was designed on Giraph++ which is a semi-asynchronous parallel graph computation framework running on distributed environment. In the algorithm, a network of large size is firstly divided into a number of small sub-networks. Then, each sub-network is modeled as a self-evolving swarm intelligence sub-system, while each vertex within the sub-network acts iteratively to join into or leave from communities based on a set of predefined vertex action rules. Meanwhile, the local communities of a sub-network are sent to other sub-networks to make their members have a chance to join into, therefore connecting these self-evolving swarm intelligence sub-systems together as a whole, large and evolving, system. The vertex actions during evolution of a sub-network are sent as well to keep multiple community replicas being consistent. Thus network communication efficiency has a great impact on the algorithm’s performance. While there is no vertex changing in its belonging communities anymore, an optimal community structure of the whole network will have emerged as a result. In the algorithm it is natural that a vertex can join into multiple communities simultaneously, thus can be used for overlapping community detection. The algorithm deals with vertex and edge adding or deleting in the same way as the algorithm running, therefore inherently supports dynamic network analysis. The algorithm can be used for the analysis of large scale networks with its parallel version running on distributed environment. A variety of experiments conducted on synthesized networks have shown that the proposed algorithm can effectively detect community structures and its performance is much better than certain popular community detection algorithms